数据来源：ArXiv Domain LLM Domain Papers1. TokenScope: Token-Level Explainability and Interpretability for Code-Oriented Tasks in Large Language ModelsAbstract:Understanding how Large Language Models (LLMs) make token-level decisions during code generation remains a major challenge for both researchers and practitioners. While recent tools provide insights into model internals or generation outcomes, they often lack decoding-time signals, fine-grained uncertainty measures, and interactive mechanism ...

数据来源：ArXiv Domain LLM Domain Papers1. TokenScope: Token-Level Explainability and Interpretability for Code-Oriented Tasks in Large Language ModelsAbstract:Understanding how Large Language Models (LLMs) make token-level decisions during code generation remains a major challenge for both researchers and practitioners. While recent tools provide insights into model internals or generation outcomes, they often lack decoding-time signals, fine-grained uncertainty measures, and interactive mechanism ...

数据来源：ArXiv Domain LLM Domain Papers1. Unveiling Public Opinion: A Study of Sentiment Analysis Using LSTM and Traditional ModelsAbstract:In this age of social media, sites like Twitter have become meeting places for people to share their views and feelings on a wide range of issues and current events as they unfold in real time. Sentiment analysis, a critical application of NLP, has become indispensable due to the massive influx of user-generated content, enabling the extraction of meaningful i ...

数据来源：ArXiv Domain LLM Domain Papers1. Just Keep Prompting: Evaluating Repetitive Socratic Prompting in VLMsAbstract:Deploying Vision-Language Models (VLMs) in real-world settings requires not only strong visual reasoning but also stability under sustained conversational pressure. We introduce Just Keep Prompting (JKP), a multi-turn evaluation framework that measures VLM epistemic stability when users repeatedly challenge, question, or contradict a model’s answer. JKP probes models for up to 10 ...

数据来源：ArXiv Domain LLM Domain Papers1. Just Keep Prompting: Evaluating Repetitive Socratic Prompting in VLMsAbstract:Deploying Vision-Language Models (VLMs) in real-world settings requires not only strong visual reasoning but also stability under sustained conversational pressure. We introduce Just Keep Prompting (JKP), a multi-turn evaluation framework that measures VLM epistemic stability when users repeatedly challenge, question, or contradict a model’s answer. JKP probes models for up to 10 ...

数据来源：ArXiv Domain LLM Domain Papers1. What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning TracesAbstract:What makes writing “good” remains a persistent question in literary studies and computational linguistics. We present a two-study investigation of how reasoning-enabled LLMs evaluate literary quality. In Study 1, we construct a benchmark of 30 real texts spanning six quality tiers, from canonical literature to anonymous forum posts, and extract the ...

数据来源：ArXiv Domain LLM Domain Papers1. What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning TracesAbstract:What makes writing “good” remains a persistent question in literary studies and computational linguistics. We present a two-study investigation of how reasoning-enabled LLMs evaluate literary quality. In Study 1, we construct a benchmark of 30 real texts spanning six quality tiers, from canonical literature to anonymous forum posts, and extract the ...

数据来源：ArXiv Domain LLM Domain Papers1. Prompt Chaining in Practice: A Case Study in Automated Scholarly Report GenerationAbstract:The exponential growth of scholarly publications requires automated tools for effective information synthesis. However, simple, single-shot prompting methods often lack the reliability and quality required for complex synthesis tasks. This paper introduces and empirically evaluates a multi-stage prompt chaining methodology as a more reliable architectural pattern for ...

数据来源：ArXiv Domain LLM Domain Papers1. Prompt Chaining in Practice: A Case Study in Automated Scholarly Report GenerationAbstract:The exponential growth of scholarly publications requires automated tools for effective information synthesis. However, simple, single-shot prompting methods often lack the reliability and quality required for complex synthesis tasks. This paper introduces and empirically evaluates a multi-stage prompt chaining methodology as a more reliable architectural pattern for ...